MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641106327 A) filed by Vallurupalli Nageswara Rao Vignana Jyothi Institute Of Engineering And Technology on September 03, 2026, for A Personality-Aware Predictive Cloud Auto-Scaling System With Adaptive Resource Allocation And Intelligent Workload Behaviour Analysis.
Inventors include Dr. N. Praveen Kumar; Dr. D. Manju; Addepalli Haasini Varma; S. Mithilesh; S. Sahasra Reddy; and B. Nandhini Reddy.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention relates to ProMood, a personality-aware predictive cloud auto scaling system and method. Workload telemetry is monitored and converted into temporal behavioural features including burst ratio, idle duration, spike frequency, periodicity, time-of-day encoding, execution density, and resource utilisation trends. A workload personality engine generates a workload personality vector, which is supplied to a prediction layer for forecasting future demand using LSTM, GRU, transformer, temporal convolutional network, graph neural network, reinforcement learning, statistical, ensemble, hybrid, or equivalent future predictive engines. An adaptive threshold generator produces scaling thresholds based on personality, predicted demand, forecast confidence, provisioning latency, cost policy, and service- level objectives. An intelligent scaling controller issues proactive scaling actions to a cloud orchestrator before overload occurs. The system further includes behavioural fingerprinting, behaviour evolution, historical behaviour storage, resource optimisation, model update, feedback, continuous learning, explainability, policy optimisation, security, edge computing, multi-cloud deployment, and hybrid cloud compatibility. The invention supports Kubernetes, virtual machines, serverless environments, edge deployments, hybrid clouds, multi-cloud infrastructures, AI inference systems, and GPU clusters. By continuously updating workload personalities and adapting prediction and scaling decisions, the invention improves resource utilisation, reduces service degradation, limits over-provisioning, and enables explainable, policy-aware, proactive cloud auto scaling. The invention uses a cloud monitoring layer, behavioural fingerprint generator, workload personality engine, prediction layer, adaptive threshold generator, decision intelligence engine, intelligent scaling controller, resource optimisation module, cloud orchestrator, model update engine, historical behaviour database, feedback layer, continuous learning layer, explainability layer, policy optimisation layer, security layer, edge computing layer, multi-cloud deployment layer, and hybrid cloud compatibility layer. The invention is applicable to Kubernetes, container platforms, virtual machines, serverless systems, GPU clusters, edge nodes, public cloud, private cloud, hybrid cloud, and multi-cloud infrastructure.
Disclaimer: Curated by HT Syndication.
